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Optimization & Theory

36,874 papers (3 classified directly here)

Subtopics

Optimization (14,983) Bayesian Inference (5,566) Learning Theory (5,334) Theory (4,955) Statistical Learning (4,117) Neural Network Optimization (3,649) Stochastic Processes (2,667) Loss Functions (1,162) Distributed Learning (1,135) Stochastic Methods (1,118) Online Algorithms (806) Statistics (684) Information Theory (318) Generalization (220) Sparse Optimization (158) Sample Complexity (99) Game Theory (30) Robust Optimization (17) Optimal Transport (14) Approximation Algorithms (10) Distributed Optimization (8) Convex Optimization (8)

Papers per year

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Papers (including subtopics)

Simplifying Latent Dynamics with Softly State-Invariant World Models NIPS 2024
Activating Self-Attention for Multi-Scene Absolute Pose Regression NIPS 2024
Bias Amplification in Language Model Evolution: An Iterated Learning Perspective NIPS 2024
Credal Learning Theory NIPS 2024
On the Power of Small-size Graph Neural Networks for Linear Programming NIPS 2024
Generative Hierarchical Materials Search NIPS 2024
Certified Machine Unlearning via Noisy Stochastic Gradient Descent NIPS 2024
$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling NIPS 2024
Gated Inference Network: Inference and Learning State-Space Models NIPS 2024
FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning NIPS 2024
Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps NIPS 2024
Sample Complexity of Interventional Causal Representation Learning NIPS 2024
Dual-Personalizing Adapter for Federated Foundation Models NIPS 2024
Group-wise oracle-efficient algorithms for online multi-group learning NIPS 2024
Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models NIPS 2024
An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem NIPS 2024
The Sample-Communication Complexity Trade-off in Federated Q-Learning NIPS 2024
Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions NIPS 2024
On Differentially Private Subspace Estimation in a Distribution-Free Setting NIPS 2024
Optimal Scalarizations for Sublinear Hypervolume Regret NIPS 2024
Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data NIPS 2024
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks NIPS 2024
Quasi-Bayes meets Vines NIPS 2024
Online Learning with Sublinear Best-Action Queries NIPS 2024
On the Target-kernel Alignment: a Unified Analysis with Kernel Complexity NIPS 2024